In business and economics, decentralization often refers to the ability to participate in a market and exchange value between peers without the interference of a third-party intermediary who most likely controls and restricts barriers of entry. As Ethereum co-founder Vitalik Buterin explains in his blog post “The Meaning of Decentralization,” blockchain is politically and architecturally decentralized, meaning no entity one controls it and there’s no central point of failure in its infrastructure. In this way, a decentralized supply chain would allow for a frictionless vehicle of business-to-business value exchange amongst even the smallest players in the industry.

Decentralization is defined as the transfer of power away from a central location or authority. As a concept, it is not new; as a business model, however, it is a powerful idea. Some sociologists claim that decentralization and centralization theories have actually been occurring in cycles for the last 4,000 years, causing the rise and subsequent fall of ruling states and empires. Throughout history, the core theory behind decentralization has remained the same: dispersing power from authorities and empowering smaller, individual entities with the ability to act in their own self-interest.

Why decentralization is necessary for modern supply chains

This is especially necessary in the supply chain industry, which has historically suffered from a number of issues that hinder its efficiency. Its main roadblock is that current supply chains are unable to become agile, which poses a significant problem in a market in which they must be able to change their configurations quickly and continually to meet the constantly-changing dynamics of supply and demand. Another major disadvantage is that methods of communication tend to vary greatly, with some companies still relying on manual paperwork. As a result, data storage becomes locked away in in proprietary systems that don’t allow for collaboration.

Supply chain companies also tend to face cultural and organizational issues, such as executing operating plans due to corporate goals, board restrictions and the competitive nature of the market. Consequently, companies have revoked social contracts, mistreated skilled laborers and underutilized their professional talent assets.

This mismanagement has serious financial consequences: for instance, $4.2 trillion is locked up in net working capital in today’s supply chains. By allowing today’s virtual supply chains to break from the company-centric, server-based environments in which they currently find themselves, they will become less brittle, more scalable and fully leverage the underutilized skills and assets available in modern-day business networks. Even a 1% improvement in Invoice-to-Cash cycle times would immediately return about $42 billion in cash to operations.

How can blockchain remedy the issues of centralization in supply chains?

When looking at its positive implications, blockchain is the most logical next step for supply chain managers and logistics providers. Blockchain was brought to the mainstream through cryptocurrencies like bitcoin and Ethereum. It creates an unchangeable digital ledger that provides a record of financial transactions in chronological order. This technology has been increasingly adapted to address gaping deficiencies in other fields, from education to voting to real estate. Through blockchain, massive networks of decentralized autonomous individuals and organizations can grow and operate seamlessly within a decentralized, distributed operating platform.

Blockchain also provides an efficient and viable solutions to the aforementioned hurdles that are restricting today’s supply chain. Specifically, it offers opportunities to synchronize processes that occur within supply networks, resulting in reduced Cost-of-Goods-Sold (COGS) and more cash freed from working capital.

The solution to many of these recurring issues in supply chain primarily involves people. By creating networks of skilled individuals and decentralized autonomous organizations, immense value can be brought to companies, supply chains, and customers. These networks align economic incentives so that everyone prospers, based on their contributions of time, skill, and intellectual property. These contributions are monitored and administered through outcome-based smart contracts on the blockchain. This new vision of decentralization has the potential to radically transform the supply chain space.

I’m sharing insights from Jennifer Woofter, chief-consultant at Strategic Sustainability Consulting. Interesting perspective in addressing the management of change which can often be much larger than the green-change initiative.

Change can be difficult. Whether it’s a shift at work or in your personal life, embracing change can be a challenging issue for many people. For companies moving toward greening the workplace, it’s key that they remember that even small changes can result in small stressors to employees. It’s important to recognize the added stress and think from employees’ perspectives during the transition. Organizations that are working to be more adaptive and innovative may find that the resulting culture change becomes a huge roadblock to their efforts as employees resist or respond to the stress.

Innovation and change require leaders and employees alike to embrace new behaviors, which may initially seem antithetical to existing corporate culture. When making such dramatic shifts, it’s vital that leadership understands it’s impossible to dictate optimism, trust, conviction or creativity and consider the needs of everyone in the company.

With that in mind, the entire team should work together to establish a joint purpose and utilize internal efforts to make sure everyone on the team is onboard before changes begin.

One of the best ways to motivate employees, particularly during a transition is praise. Praising people not only motivates them, it also encourages and inspires them to do even better.

If you are helping to lead a cultural movement toward a greener workplace, consider these tips:

1. Frame the issue in a way that will excite your employees and motivate them to action. In order to engage your team’s commitment you have to inspire a desire and responsibility to change. A good organizational purpose calls for the pursuit of greatness in service of others and asks employees to be driven by more than simply personal gain.

2. Demonstrate quick wins that can show how actions toward change are working. Instead of simply declaring the culture shifts you want to see, highlight examples of the actions you expect to see more of in the company.

3. Create safe havens. If you intend for individual to act differently, you might find that changing their surroundings in order to support new behaviors to be incredibly helpful. Outposts and labs are often built as a way to give people a safe space to embrace new beliefs.

4. Embrace symbols that will help create a feeling of solidarity and demarcate who your employees are and what they stand for to the outside world. Symbols can help define the boundary between “us” and “them” for movements and can be as simple as a T-shirt, bumper sticker, or button supporting a general cause, or more elaborate like a new corporate brand identity. Internally and externally, such an act can reinforce a message of unity and commitment — that an entire company stands together in pursuit of a singular purpose.

It’s important to remember that even with the best guidelines, and the best intentions, change isn’t easy. While harmony tends to be most people’s preferred environment at work, a moderate amount of friction should be considered positive during a transition. Creating a culture shift with a complete absence of friction probably means that very little has actually changed. So explore the places where change faces resistance in your office. These areas may indicate where the dominant organizational design and culture need to evolve.

And culture change can only happen when people take action. While articulating a mission and changing company structures are important, keep on tackling the tough issues after you’ve shown people the change you want to see.

Sharing point of view from Greg Brady is the CEO and founder of One Network Enterprises, a global provider of a secure and scalable multi-party business network. For more information, contact the author at gbrady@onenetwork.com or visit http://www.onenetwork.com. Enjoy!

There’s a lot of buzz and hype about artificial intelligence (AI) in supply chain management (SCM). That’s understandable given its potential. AI can offer a huge benefit to supply chain managers, but only if it is based on solid fundamentals that take into account the diverse and dynamic nature of today’s modern supply chains. More importantly, it needs to consider the availability of the timely and accurate data needed to make smart decisions.

Before addressing what AI can do, it is critical to first understand what it is. In the simplest terms, AI is intelligence exhibited by machines, or when machines mimic or can replace intelligent human behavior, such as problem solving or learning. In essence, AI is machines making decisions whether that is deciding which chess piece to move where, or how to adjust an order forecast based on changing demand.

Despite its benefits, when looked at through the lens of a supply chain executive, AI is relatively useless unless it’s able to add value to support better decision-making.

Why AI Hasn’t Delivered in SCM

In the race to use AI, many companies have made attempts to implement it, but the results have been disappointing. This is because typical SCM systems today:

Require armies of expensive planners

Run complex engines at each step in the process and at each node in the supply network

Are usually in conflict with other functions and/or partners

Miss huge opportunities hidden in the network because they are locally sub optimized

Work on stale data and thus promote bad decisions

Use dumbed-down, over-simplified problem models that do not relate to the real world

These SCM limitations have severely suppressed return on AI investments. For example, typical Retail/CPG supply chains still carry 60-75 days of inventory. The average service level in the store is about 96 percent, with promoted item service levels much lower at the 80 percent range. The Casual Dining segment on the other hand, carries around 12 – 15 days of inventory with relatively high waste and high cost-of-goods-sold. So, unless AI can make a significant impact on these metrics, it’s simply not delivering.

Key Requirements for AI in Supply Chain Management

Having worked with hundreds of supply chain executives, on dozens of software implementations, I’ve studied the AI issue a lot. What I have found is there are eight criteria that are required for a successful AI implementation. Miss one of these and you’ll be lucky to achieve mediocre outcomes, but when you meet them all, you can indeed achieve world class results. For the AI solution to offer optimal value in supply chain, it important to ensure the following:

1. Access to Real-Time Data
To improve on traditional enterprise systems with older batch planning systems, new AI systems must eliminate the stale data problem. Most supply chains today attempt to execute plans using data that is days old, but this results in poor decision-making that sub-optimizes the supply chain, or requires manual user intervention to address. Without real-time information, an AI tool is just making bad decisions faster.

2. Access to Community (Multi-Party) Data
The ability to access data outside of the enterprise or, more importantly, receive permission to see the data that is relevant to your trading community, must be made available to any type of AI, Deep Learning or Machine Learning algorithms.

Unless the AI tool can see the forward-most demand and downstream supply, and all relevant constraints and capacities in the supply chain, the results will be no better than that of a traditional planning system. Unfortunately, this lack of visibility and access to real-time, community data is the norm in over 99 percent of all supply chains. Needless to say, this must change for an AI tool to be successful.

3. Support for Network-Wide Objective Functions
The objective function, or primary goal, of the AI engine must be consumer service level at lowest possible cost. This is because the end-consumer is the only consumer of true finished goods products. If we ignore this fact, trading partners will not get the full value that comes from optimizing service levels and cost to serve, which is obviously important as increased consumer sell-through drives value for everyone.
A further enrichment of the decision algorithm should support enterprise level cross-customer allocation to address product scarcity issues and individual enterprise business policies. Thus, AI solutions must support global consumer-driven objectives even when faced with constraints within the supply chain.

4. Decision Process Must Be Incremental and Consider the Cost of Change
Re-planning and changing execution plans across a networked community in real time can create nervousness in the community. Constant change without weighing the cost of the change creates more costs than savings and reduces the ability to effectively execute. An AI tool must consider trade-offs in terms of cost of change against incremental benefits when making decisions.

5. Decision Process Must Be Continuous, Self-Learning and Self-Monitoring
Data in a multi-party, real-time network is always changing. Variability and latency is a recurring problem, and execution efficiency varies constantly. The AI system must be looking at the problem continuously, not just periodically, and should learn as it goes on how to best set its own policies to fine tune its abilities. Part of the learning process is to measure the effectiveness “analytics,” then apply what it has learned.

6. AI Engines Must Be Autonomous Decision-Making Engines
Significant value can only be achieved if the algorithm can not only make intelligent decisions but can also execute them. Furthermore, they need to execute not just within the enterprise but where appropriate, across trading partners. This requires your AI system and the underlying execution system to support multi-party execution workflows.

7. AI Engines Must Be Highly Scalable
For the supply chain to be optimized across an entire networked community of consumers to suppliers, the system must be able to process huge volumes of data very quickly. Large community supply chains can have millions if not hundreds of millions of stocking locations. AI solutions must be able to make smart decisions, fast, and on a massive scale.

8. Must Have a Way for Users to Engage with the System
AI should not operate in a “black box.” The UI must give users visibility to decision criteria, propagation impact, and enable them to understand issues that the AI system cannot solve. The users, regardless of type, must to be able to monitor and provide additional input to override AI decisions when necessary. However, the AI system must drive the system itself and only engage the user on an exception basis, or allow the user to add new information the AI may not know at the request of the user.

AI in the Real World Today

Sounds good in theory, but how does it work out in practice? Now that we have addressed the key fundamentals, let’s look at how some actual companies have achieved applying these criteria.

For instance, one of the major problems in Casual Dining is anticipating and meeting demand for the restaurants, corporate owned or franchised. This is especially important during Limited Time Offers (LTOs). Using the eight criteria outlined above, a global, casual dining company connected to a real-time, multi-party network, and was able to rapidly achieve their objective function – excellent customer service at the lowest cost.

The company constantly monitors Point-of-Sale (POS) data, and is using AI agents to recognize and predict consumption patterns of consumers. In addition, intelligent AI agents create the demand forecast and then compare it to the actual demand in real-time. When there is significant deviation, the agents make the decision to adjust the forecast, and additional agents adjust replenishments. They then propagate those adjustments across the supply chain to trading partners in real time at all times considering the cost of change and the propagation impact.

This drove a remarkable improvement in forecast accuracy. During promotions, the company achieved over 85 percent forecast accuracy at the store level and even higher at the DC level. This represents at least a 25 percent improvement over traditional approaches.

Intelligent agents also optimize restaurant orders autonomously by recognizing the impact of projected restaurant traffic trends and impact on LTOs and therefore the orders. The system runs on an exception basis but allows the managers to review the decision criteria and override orders where the managers may have local information such as inventory issues or local store traffic issues. This has resulted in much faster order placement and order accuracy of over 82 percent, which reduces both inventory and waste dramatically while increasing service levels to the consumer. This is a significant improvement to all other known implementations in the marketplace.

Because the algorithms are highly scalable, they are processing over 15 million stocking locations continuously throughout the day.

Prior to the AI-based, multi-party execution system, restaurant managers had to interact with nine different ordering systems and manually create their own orders based on general guidelines, rules of thumb, and spreadsheet-based or manual calculations.

With AI implemented on a sound foundation, this company can now anticipate, manage, and serve demand at the lowest possible cost. During LTO’s, when demand fluctuations would overwhelm a restaurant manager, intelligent agents monitor demand in real time, and autonomously orchestrate the supply chain to align supply with demand. Thus, the company can meet its goal and maintain high service levels while reducing cost to serve.

These are not isolated results. Also in the food marketplace, another CPG-Retail implementation achieved 99 percent in-stock, in-store, with 25 days of supply (DOS) across the supply chain. The inventory results are less than half the standard DOS in this marketplace and 3 percent points higher in in-store in-stocks
AI-based solutions are being deployed at two large automotive tier one suppliers with results ranging from 16 – 40 percent reductions in inventory as well as significant reductions in expedited freight costs.

AI Delivers Value in SCM Today

As you can see, laying the proper groundwork for AI pays huge dividends. There’s no doubt that AI offers even greater promise in the future, but, as these results show, there are significant benefits and dramatic results waiting for companies that focus on the fundamentals and put AI to use today.

The beauty of AI-based solutions is that they learn and drive continuous improvement over time. They get more precise and sophisticated as they gather more data and more experience. The sooner you start, the better the results you’ll see in future, and the further ahead you will be. With the right AI solution in place, you can outpace your competitors today, and be well positioned for reaping even bigger rewards of AI’s promise tomorrow. ~Greg Brady

As we confront a new political climate that is inspiring both uncertainty and rising citizen action, I am more convinced than ever that business must play a critical role in achieving a sustainable, equitable and clean-energy future. Bold leadership, as well as individual and collective action from influential companies and investors, is critical to ensure continued progress in achieving the ambitions of the historic Paris Climate Agreement and the U.N. Sustainable Development Goals.

Fortunately, companies we engage with here at Ceres continue to demonstrate that sustainability is not just good for the bottom line; it is the bottom line. Despite backward steps in Washington, there is unprecedented clarity in the business community – especially from the Fortune 100s – that building a healthy, low-carbon economy is irresistible and irreversible. Examples of this are popping up everywhere, although still not at the pace and scale we need.

These seven key corporate trends are ready for primetime and will be critically important in advancing our sustainability goals, no matter the political winds in Washington.

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1. Corporate support for clean-energy policy is accelerating

Corporate energy buyers want renewable energy – and not just to help them meet their own greenhouse gas reduction goals. Renewable energy prices are increasingly cost-competitive in many parts of the country, and they remove the long-term risks associated with fossil fuel energy price volatility.

More than 900 companies and investors are calling on President Trump and Congress to keep the U.S. in the Paris Climate Agreement and to support low-carbon policies in the U.S. And nearly 100 global companies have signed on to to the RE100 initiative, a commitment to source all of their energy from renewables.

Lacking a national carbon mitigation strategy, states and cities will continue to be the platforms on which we’ll see meaningful clean-energy progress. In Michigan, Ohio and Virginia, among other states, companies are helping to shape policies that strengthen and increase access to renewable energy, leading to more clean-energy investment and jobs in those states.

The Task Force on Climate-Related Disclosures (TCFD) – whose leadership includes Ceres member companies such as Bloomberg LP and JPMorgan Chase – recently published a specific guidance on how companies should evaluate and disclose climate risks in financial filings.

Investors and global stock exchanges are taking notice, especially in regard to how carbon-intensive companies are analyzing business impacts under scenarios where carbon pollution is reduced at levels that would limit global warming to 2-degrees Celsius or less – the goal of the Paris Climate Agreement.

More than ever, investors are aiming these questions at energy-intensive companies like ExxonMobil and Chevron, which are already struggling financially as global oil demand is waning.

3. Companies are advancing human rights reporting and performance

Companies are facing unprecedented scrutiny on their human rights performance and reporting. In 2015, the nonprofit group Shift that helps organizations to implement the U.N. Guiding Principles on Business and Human Rights (UNGPs), developed the UNGP reporting framework, which companies such as Ericsson, Nestle, and Unilever are already utilizing to strengthen human rights reporting and performance.

Ceres is now collaborating with Shift to advance corporate adoption and implementation of the framework to drive improved human rights performance across direct operations and global supply chains.

4. Water risks are rising on the investor agenda

Water crises such as prolonged droughts and extreme precipitation events – been in California, lately? – were again among the top five global impact risks in an annual report from the World Economic Forum.

Increasingly, companies operating in water-stressed regions are proactively taking action to conserve and protect water sources. General Mills, Gap and PepsiCo, are among a growing cadre of companies engaging with California policymakers on the urgency for stronger water management policies in this water-starved state.

5. Competence on sustainability is becoming a measure of board effectiveness

Corporate boards have a key authority and responsibility to boost corporate attention on long-term sustainability risks like climate change. Large investors are increasingly focused on the role board members can play on sustainability. U.S. pension funds CalPERSand CalSTRS, for example, both recently updated their governance principles to explicitly request that company boards have stronger experience and expertise on climate risk management.

In the coming months, investors and other stakeholders will be looking to engage with key governance experts within companies on this topic, including corporate secretaries and general counsel.

6. SDGs will be a bigger driver of strategy and action

In 2015, more than 190 world leaders committed to 17 Sustainable Development Goals (SDGs) aimed at ending extreme poverty, eliminating longstanding inequalities and fighting climate change.

Worldwide momentum behind these internationally supported goals continues to gain strength, and at the upcoming Ceres Conference we will hear from Novozymes, BASF and Intel about how they are aligning their commitments and business strategies with this global vision.

7. Sustainable sourcing is becoming the new norm

Access to reliable, affordable supplies of key inputs is threatened by climate change, water scarcity risks, and the use of unethical practices like deforestation and forced labor. Agricultural supply chains are feeling some of the biggest pressures, leading to stronger action by investors and companies themselves to push for strategies to assess and manage these risks.

This spring, Ceres will release an interactive tool called Engage the Chain to help investors and companies better understand wide-ranging agricultural commodity risks.

No doubt, company actions on all of these fronts will continue to evolve – and, hopefully, accelerate. Such leadership is more essential than ever.

It’s no secret that Amazon is revolutionizing the retail industry. But what does that actually mean?

Which retailer is Amazon targeting now? Amazon newest target isn’t a retail chain at all — it’s your local convenience store.The company rolled out a new service today called Amazon Instant Pickup, which lets customers order basics like chips, soda and toothpaste. You can then pick them up from an Amazon locker in just two minutes.

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Isn’t mimicry the sincerest form of flattery? Not if you’re a retailer that wants to stay in business. Just ask Dick’s Sporting Goods (DKS). Dick’s earnings report disappointed Wall Street on Tuesday. The retailer lowered its full-year profit forecast today because of “a challenging retail environment.” Its stock fell more than 20%. Sound familiar? Last month, Amazon filed a patent to launch a competing meal-kit delivery service. Blue Apron’s shares plunged 11% following the news. And grocery stocks got clobbered after Amazon announced plans to buy Whole Foods (WFM) for $13.7 billion back in June.

Is Amazon a death sentence for traditional retailers? Not necessarily. Retailers like Home Depot (HD) are surviving by selling things you can’t buy on Amazon. Today, Home Depot reported record sales last quarter and bolstered its outlook for 2017. Home owners and professional builders alike still prefer to go to stores to test out home products, especially big ticket items like flooring and appliances.

A NEW commodity spawns a lucrative, fast-growing industry, prompting antitrust regulators to step in to restrain those who control its flow. A century ago, the resource in question was oil. Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017. Amazon captures half of all dollars spent online in America. Google and Facebook accounted for almost all the revenue growth in digital advertising in America last year.

Such dominance has prompted calls for the tech giants to be broken up, as Standard Oil was in the early 20th century. This newspaper has argued against such drastic action in the past. Size alone is not a crime. The giants’ success has benefited consumers. Few want to live without Google’s search engine, Amazon’s one-day delivery or Facebook’s newsfeed. Nor do these firms raise the alarm when standard antitrust tests are applied. Far from gouging consumers, many of their services are free (users pay, in effect, by handing over yet more data). Take account of offline rivals, and their market shares look less worrying. And the emergence of upstarts like Snapchat suggests that new entrants can still make waves.

But there is cause for concern. Internet companies’ control of data gives them enormous power. Old ways of thinking about competition, devised in the era of oil, look outdated in what has come to be called the “data economy”. A new approach is needed.

Quantity has a quality all its own

What has changed? Smartphones and the internet have made data abundant, ubiquitous and far more valuable. Whether you are going for a run, watching TV or even just sitting in traffic, virtually every activity creates a digital trace—more raw material for the data distilleries. As devices from watches to cars connect to the internet, the volume is increasing: some estimate that a self-driving car will generate 100 gigabytes per second. Meanwhile, artificial-intelligence (AI) techniques such as machine learning extract more value from data. Algorithms can predict when a customer is ready to buy, a jet-engine needs servicing or a person is at risk of a disease. Industrial giants such as GE and Siemens now sell themselves as data firms.

This abundance of data changes the nature of competition. Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on. The more data Tesla gathers from its self-driving cars, the better it can make them at driving themselves—part of the reason the firm, which sold only 25,000 cars in the first quarter, is now worth more than GM, which sold 2.3m. Vast pools of data can thus act as protective moats.

Access to data also protects companies from rivals in another way. The case for being sanguine about competition in the tech industry rests on the potential for incumbents to be blindsided by a startup in a garage or an unexpected technological shift. But both are less likely in the data age. The giants’ surveillance systems span the entire economy: Google can see what people search for, Facebook what they share, Amazon what they buy. They own app stores and operating systems, and rent out computing power to startups. They have a “God’s eye view” of activities in their own markets and beyond. They can see when a new product or service gains traction, allowing them to copy it or simply buy the upstart before it becomes too great a threat. Many think Facebook’s $22bn purchase in 2014 of WhatsApp, a messaging app with fewer than 60 employees, falls into this category of “shoot-out acquisitions” that eliminate potential rivals. By providing barriers to entry and early-warning systems, data can stifle competition.

Who ya gonna call, trustbusters?

The nature of data makes the antitrust remedies of the past less useful. Breaking up a firm like Google into five Googlets would not stop network effects from reasserting themselves: in time, one of them would become dominant again. A radical rethink is required—and as the outlines of a new approach start to become apparent, two ideas stand out.

The first is that antitrust authorities need to move from the industrial era into the 21st century. When considering a merger, for example, they have traditionally used size to determine when to intervene. They now need to take into account the extent of firms’ data assets when assessing the impact of deals. The purchase price could also be a signal that an incumbent is buying a nascent threat. On these measures, Facebook’s willingness to pay so much for WhatsApp, which had no revenue to speak of, would have raised red flags. Trustbusters must also become more data-savvy in their analysis of market dynamics, for example by using simulations to hunt for algorithms colluding over prices or to determine how best to promote competition.

The second principle is to loosen the grip that providers of online services have over data and give more control to those who supply them. More transparency would help: companies could be forced to reveal to consumers what information they hold and how much money they make from it. Governments could encourage the emergence of new services by opening up more of their own data vaults or managing crucial parts of the data economy as public infrastructure, as India does with its digital-identity system, Aadhaar. They could also mandate the sharing of certain kinds of data, with users’ consent—an approach Europe is taking in financial services by requiring banks to make customers’ data accessible to third parties.

Rebooting antitrust for the information age will not be easy. It will entail new risks: more data sharing, for instance, could threaten privacy. But if governments don’t want a data economy dominated by a few giants, they will need to act soon.

Unlike others, with limited expectations about the impact of technology, who dream of going back to the glorious days of ERP or MRP systems, and order-based solutions, my core belief and experience, is that operational excellence comes from the introduction of new technologies, and applying them now to get on the learning curve before anyone else, and not in a distant future. We can become more agile, compress order-to-cash lead-times, and re-invent how to deliver products and services. Thus creating very new sources of competitive advantage for our customers.

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Like the German industry is proving most recently with Industry 4.0, I firmly believe that digitization, robotics, and the Internet of Things, will help us leverage the continuous data-stream from the internet, and transform the manufacturing base with new and more flexible technologies, aiming at making production planning more responsive to forecasted market changes and customer preferences.

The opportunities are unlimited. And it is the task of supply chain consultants to help companies upgrade their supply chains, introducing these new technologies, and fundamentally redefine how our supply chain and businesses operate, not with the narrow mindset of cost control, inventory reduction and efficiency gains, but rather with the ambitious goal of redefining the value equation in each industry, with a continuous eye on tangible outcomes for the customers.

The value provided to companies, is radical redesign of the processes of your company, putting the customer at the centre, and providing them a totally new level of experiences and satisfaction, contributing to better margins and increased revenue.

It will make your business:

Cheaper

Faster

More Value add

The enablers are methodologies supported by data, to redesign physical supply chain networks, and digitize the underlying processes. In today’s world, what happens in the information world, is more important than the physical product flow. Wise use of technologies can overcome any dysfunctional supply chain and help a company operate at its maximum capabilities.

The supply chain innovation is introduced by making the supply chain more customer-driven, and the business more customer-centric. These are not empty words but efforts to redesign processes providing a maximum of value to each customer, and redefining the meaning of operational excellence. Segmentation, predictive analytics and value chain orchestration are at the core of this revolution.

The operational excellence results from strategic alignment and process integration, across silos and aligning objectives and business priorities, based on customer-driven insights, across the extended supply chain, breaking walls inside and across organizations, divisions and companies, give a direct operational benefit and a step change in supply chain performance.

Powered by this vision of transforming the actors of the supply chain, into a collaborative value network, where any node can add value to the overall community, and being rewarded accordingly, supported by Industry 4.0 technologies, we can provide customers with that so much desired instant gratification, the internet and companies like Amazon have started to make a standard expectation of the new customer.

The bonus is that this customer-driven revolution also significantly improves the companies top-and bottomline performance.

That is why it is important you join this Customer-led SC revolution. Upgrade your supply chain or become less relevant, the choice is yours.

Even years into the deployment of the internet, many believed that it was still a fad. Of course, the internet has since become a major influence on our lives, from how we buy goods and services, to the ways we socialize with friends, to the Arab Spring, to the 2016 U.S. presidential election. Yet, in the 1990s, the mainstream press scoffed when Nicholas Negroponte predicted that most of us would soon be reading our news online rather than from a newspaper.

Fast forward two decades: Will we soon be seeing a similar impact from cryptocurrencies and blockchains? There are certainly many parallels. Like the internet, cryptocurrencies such as Bitcoin are driven by advances in core technologies along with a new, open architecture — the Bitcoin blockchain. Like the internet, this technology is designed to be decentralized, with “layers,” where each layer is defined by an interoperable open protocol on top of which companies, as well as individuals, can build products and services.

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Like the internet, in the early stages of development there are many competing technologies, so it’s important to specify which blockchain you’re talking about. And, like the internet, blockchain technology is strongest when everyone is using the same network, so in the future we might all be talking about “the” blockchain.

The internet and its layers took decades to develop, with each technical layer unlocking an explosion of creative and entrepreneurial activity. Early on, Ethernet standardized the way in which computers transmitted bits over wires, and companies such as 3Com were able to build empires on their network switching products. The TCP/IP protocol was used to address and control how packets of data were routed between computers. Cisco built products like network routers, capitalizing on that protocol, and by March 2000 Cisco was the most valuable company in the world. In 1989 Tim Berners-Lee developed HTTP, another open, permissionless protocol, and the web enabled businesses such as eBay, Google, and Amazon.

The Killer App for Blockchains

But here’s one major difference: The early internet was noncommercial, developed initially through defense funding and used primarily to connect research institutions and universities. It wasn’t designed to make money, but rather to develop the most robust and effective way to build a network. This initial lack of commercial players and interests was critical — it allowed the formation of a network architecture that shared resources in a way that would not have occurred in a market-driven system.

The “killer app” for the early internet was email; it’s what drove adoption and strengthened the network. Bitcoin is the killer app for the blockchain. Bitcoin drives adoption of its underlying blockchain, and its strong technical community and robust code review process make it the most secure and reliable of the various blockchains. Like email, it’s likely that some form of Bitcoin will persist. But the blockchain will also support a variety of other applications, including smart contracts, asset registries, and many new types of transactions that will go beyond financial and legal uses.

We might best understand Bitcoin as a microcosm of how a new, decentralized, and automated financial system could work. While its current capabilities are still limited (for example, there’s a low transaction volume when compared to conventional payment systems), it offers a compelling vision of a possible future because the code describes both a regulatory and an economic system. For example, transactions must satisfy certain rules before they can be accepted into the Bitcoin blockchain. Instead of writing rules and appointing a regulator to monitor for breaches, which is how the current financial system works, Bitcoin’s code sets the rules and the network checks for compliance. If a transaction breaks the rules (for example, if the digital signatures don’t tally), it is rejected by the network. Even Bitcoin’s “monetary policy” is written into its code: New money is issued every 10 minutes, and the supply is limited so there will only ever be 21 million Bitcoins, a hard money rule similar to the gold standard (i.e., a system in which the money supply is fixed to a commodity and not determined by government).

This is not to say the choices Bitcoin currently offers are perfect. In fact, many economists disagree with Bitcoin’s hard money rule, and lawyers argue that regulation through code alone is inflexible and doesn’t permit any role for useful discretion. What cannot be disputed, however, is that Bitcoin is real, and it works. People ascribe real economic value to Bitcoins. “Miners,” who maintain the Bitcoin blockchain, and “wallet providers,” who write the software people use to transact in Bitcoin, follow the rules without exception. Its blockchain has remained resilient to attack, and it supports a robust, if basic, payment system. This opportunity to extend the use of the blockchain to remake the financial system unnerves and enthralls in equal measure.

Too Much Too Soon?

Unfortunately, the exuberance of fintech investors is way ahead of the development of the technology. We’re often seeing so-called blockchains that are not really innovative, but instead are merely databases, which have existed for decades, calling themselves blockchains to jump on the buzzword bandwagon.

There were many “pre-internet” players, for example telecom operators and cable companies trying to provide interactive multimedia over their networks, but none could generate enough traction to create names that you would remember. We may be seeing a similar trend for blockchain technology. Currently, the landscape is a combination of incumbent financial institutions making incremental improvements and new startups building on top of rapidly changing infrastructure, hoping that the quicksand will harden before they run out of runway.

In the case of cryptocurrencies, we’re seeing far more aggressive investments of venture capital than we did for the internet during similar early stages of development. This excessive interest by investors and businesses makes cryptocurrencies fundamentally different from the internet because they haven’t had several decades of relative obscurity where noncommercial researchers could fiddle, experiment, iterate on, and rethink the architecture. This is one reason why the work that we’re doing at the Digital Currency Initiative at the MIT Media Lab is so important: It is one of the few places a substantial effort is being made to work on the technology and infrastructure clear of financial interests and motivations. This is critical.

The existing financial system is very complex at the moment, and that complexity creates risk. A new decentralized financial system made possible with cryptocurrencies could be much simpler by removing layers of intermediation. It could help insure against risk, and by moving money in different ways could open up the possibility for different types of financial products. Cryptocurrencies could open up the financial system to people who are currently excluded, lower barriers to entry, and enable greater competition. Regulators could remake the financial system by rethinking the best way to achieve policy goals, without diluting standards. We could also have an opportunity to reduce systemic risk: Like users, regulators suffer from opacity. Research shows that making the system more transparent reduces intermediation chains and costs to users of the financial system.

The Takeaway

The primary use and even the values of the people using new technologies and infrastructure tend to change drastically as these technologies mature. This will certainly be true for blockchain technology.

Bitcoin was first created as a response to the 2008 financial crisis. The originating community had a strong libertarian and antiestablishment spin that, in many ways, was similar to the free-software culture, with its strong anticommercial values. However, it is likely that, just as Linux is now embedded in almost every kind of commercial application or service, many of the ultimate use cases of the blockchain could become standard fare for established players like large companies, governments, and central banks.

Similarly, many view blockchain technology and fintech as merely a new technology for delivery — maybe something akin to CD-ROMs. In fact, it is more likely to do to the financial system and regulation what the internet has done to media companies and advertising firms. Such a fundamental restructuring of a core part of the economy is a big challenge to incumbent firms that make their living from it. Preparing for these changes means investing in research and experimentation. Those who do so will be well placed to thrive in the new, emerging financial system.

The adult beverage industry is transforming as the ‘Internet of Things’ revolutionizes everything from packaging to how we order drinks.

Smart technology is profoundly influencing the way people buy and consume things across every category, and the alcohol segment in no different. We can be sure that in the very near future it will be impossible to imagine how we functioned in a world of ‘dumb’ disconnected products. It has been reported by the World Economic Forum that the overall number of connected devices is expected to double within the next four years, from 22.9 billion in 2016 to 50.1 billion by 2020.

In this nascent era of connectivity, new devices help us buy our favorite products more efficiently and new packaging informs us about everything from terroir to tampering. Brands can utilize the data collected from smart systems to improve their products and tailor them to consumer tastes. With an eye on innovation and efficiency, smart technology developers are quickly revolutionizing the way we live – and drink.

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Smart On-Premise Devices

Two new products allow imbibers to replenish their drinks on-premise without waiting at the bar. Bacardi-owned Martini recently launched a new Smart Cube that communicates with bar staff when it’s time to pour another drink. The device is added to a customer’s drink like an ice cube and then monitors the drink level in real time. It also keeps track of how many drinks have been consumed to prevent over-serving.

Malibu recently introduced their ‘Coco-nect’ cups which allow consumers to place an order for a new drink by simply twisting the base of the cup. The cup sends the order to the bar while also pinpointing the customer’s location so that the drink can be delivered to them. Once the order has been received by a bartender, the bottom of the cup changes color to let the client know that their drink is on its way.

Iowa-based startup FliteBrite has created smart beer flight paddles that help drinkers keep track of which beer they’re trying. The device also connects to an interactive app that gives detailed information about each brew. While it doesn’t currently offer the option to order more beer, one imagines that this is the next step for devices such as the FliteBrite.

Tel Aviv-based startup Glassify have developed a line of ‘smart glasses’ embedded with an NFC chip that work with a smartphone app to offer consumers incentives like free chasers, happy hour specials or food combos. The app also hooks into a bank account, allowing customers to buy drinks for their friends or go out without their wallet. While it’s fun for consumers, the glasses could also be a boon for businesses interested in tracking specifics about their sales, from what time of day certain beers sell best to which brews are more likely to be drunk in sessions.

Several companies have introduced innovations to draught systems that provide businesses with helpful analytics. TAPP is a cloud-based battery-powered smart tap handle that can track beer sales in real-time and report the timestamped data back to beermakers. The system also has options for consumer interaction, either through their smartphones or through screens in the bars.

Indiana-based start-up SteadyServ offers a similar cloud-based system that helps outlets keep track of inventory, letting them know when something needs to be reordered or if a keg will need to be changed soon. The start-up’s technology uses electronic tags to identify each beer and puts a scale under each keg. The scale monitors beer levels, giving bars essential information about what is trending or what to run on special (for example, if a keg is getting old). Nevertheless, the exciting aspect for consumers is that SteadyServ integrates with social media, letting beer fans know what’s freshly on tap and what’s about to run out at their favorite pub.

European technology company WeissBeerger has created a similar smart bar system. With the goal of “turning drinks into data,” WeissBeerger offers an integrated Beverage Analytics Hub that connects with coordinating smart bar devices via cloud technology. From monitoring keg freshness and temperature controls to consumption data, the company helps businesses serve their customers more efficiently.

Smart Home Devices

Molson Coors has taken a page from Amazon’s book and launched a connected button that allows consumers to easily order more Carling beer in the UK. Similarly to the Amazon Dash button, the Carling Beer Button syncs with an accompanying smartphone app. When pressed, it adds Carling beer to an online shopping basket at one of four retailers, Tesco, Asda, Morrisons and Sainsbury’s.

Bud Light created a smart mini fridge for the California market which holds up to 78 beers. The branded connected appliance connects with an app via wifi to let consumers know when supplies are running low. The app is also programmable with user’s favorite sports teams, allowing them to receive updates when game day is approaching. The app integrates with the beer-delivery service Saucey, allowing users to order beer for delivery in Los Angeles, San Francisco and San Diego.

In Canada, The Bud-E Fridge is part of their Goal Lab range of smart offerings which also include the Goal Lamp Glasses.

Pernod Ricard recently launched 45,000 NFC-enabled smart bottles for its Malibu coconut rum brand in the UK. Consumers can access digital content and experiences by tapping their NFC-enabled android phone on the bottle’s sunset image. Content includes instant-win competitions, user-generated content competitions, drink recipes, a bar locator service and a music playlist. The connected bottles are available exclusively through Tesco.

Several brands have utilized smart bottles that can be authenticated and tracked in order to combat the uptick of counterfeit wine and spirits. Ferngrove Wine Group, Johnnie Walker Blue Label and Barbadillo sherry have both turned to Thinfilm enhanced bottles that monitor whether a bottle has been opened and wirelessly communicates with a coordinating app. The Thinfilm carries tagged information with unique identifiers that allow brands to authenticate and track their products, even after the factory seal is broken. Thinfilm can also be used to communicate product information to consumers through their smartphones.

Medea Vodka created a fun party trick with their bluetooth enabled bottles with customizable LED message bands. The bottles can be programmed with a bespoke message that will scroll across the band. Messages are controlled through an app developed by the Medea team. The app knows which bottles are nearby and available to be registered. Once a bottle is registered to one phone it cannot be controlled by anyone else. The customizable bottles allow users to create their own messages for any social occasion.

What’s Next

As our belongings become more connected, we will develop the expectation that these devices will take care of our everyday chores. For instance, a refrigerator could be programmed to automatically reorder beer once supplies drop to a pre-programmed level.

Smart sensors and devices help us collect data and buy and sell more efficiently. What will we do with all of this data? The biggest boon coming from the ‘internet of things’ is the amount of intelligence we are gathering that will drive innovation and inspire new products and services.

Abe Lincoln once told a story about a frontiersman who had lost his way in an uninhabited region on a dark and stormy night. The rain was torrential and was accompanied by terrible thunder and lightning that encased the evening sky like an electric spider web. To increase his trouble his horse halted, being exhausted with fatigue and fright. Just then a bolt of lightning struck a neighboring tree, and the ensuing crash finally brought the man to his knees. He was not an expert in prayer, but his appeal was short and to the point: “Oh, good Lord, if it is all the same to you… give us a little more light, and a little less noise.”

Small to mid-size manufacturing companies sense they are in trouble. Customers want more—more variety, more convenience, more flexibility and more service. Yet satisfying them adds even more cost and complexity at a time when pressures are felt from tight labor and increasing raw material prices. Big players have steadily acquired new skills needed to identify and capture the difficult improvements. But with fewer resources, smaller companies aren’t always able to run the business and keep up with the competition at the same time.

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To make matters worse, the manufacturing industry is awash with wonky jargon that serves to complicate and intimidate as much as it does educate. Businesses without legions of in-house resources must worry about how to adopt “circular economy” business models, migrate to “smart” manufacturing, leverage Industry 4.0 technologies, and harness the Internet of Things. Whitepapers by consulting firms swirl about in a never-ending vortex looking for a desk to land on.

In short, there is a lot of noise out there, but not so much light.

The companies that continue to achieve competitive distance do so because they drive only those supply chain improvements that truly matter to the customer and the bottom line. Those that are falling behind don’t necessarily need to “digitize” their supply chains as much as they need to stop making tradeoffs between functional competencies. For example, heads of manufacturing try to rationalize overcapacity issues in their plants, procurement officers consolidate their purchasing to leverage scale, and logistics managers seek to cut costs and improve delivery rates at their scattered warehouses. Such piecemeal efforts, however, won’t make much difference unless they’re part of a broader operational-improvement effort.

Too often, improvement in one area translates into chaos in another.

The answers for small operators who don’t have the resources to keep up with the Joneses lie not in adopting management fads but in shoring up common areas of opportunity that are ripe in value. Businesses that can execute these supply chain strategies have an opportunity to become the overall market leaders.

Minimize Self-imposed Volatility

If there is one common headache shared across all businesses, it is missed forecasts. There are, as the old joke goes, two methods to get an accurate forecast, but neither one works. A big reason for this is that forecasts are typically cannonballed by two forces of volatility: one that is market-driven and the other that is self-induced. Companies that have straightened out their forecasting woes have rooted out their own volatility drivers.

One real example: Company A discovered that 30% of its forecasting problems stemmed from stockouts. Upon further review, the underlying reason for the outages was the plants had no knowledge of sales promotions and thus had little reason to create inventory. The takeaway was to minimize the self-inflicted chaos and then invest in reactive measures like production flexibility to handle the rest.

Prioritize Key Customer/Product Combinations

Collaborations between customer and manufacturer have proliferated in recent years as supply chain improvements have become exponentially harder to come by. Companies without a sales and operations planning group can barely find the time to find the right mix of products and services to protect their customer bases.

However, in a short amount of time (at little to no investment), an operator of any size can implement a “consumer value” approach, which means that customers are prioritized based on profitability and strategic importance while also sorting products on volume demand variability. The “sweet spot” focus for the business is found at the intersection of these products and customers, which should then be serviced at the highest priority.

Periodically Redesign Your Logistics Network

Conventional wisdom states that concentrating inventory in fewer distribution centers leads to inventory savings. However, centralization usually increases logistics costs from underutilized capacity and longer distances. Given the significant position of transport costs on most P&Ls, suppliers can’t afford to ignore inefficiencies in their logistics operations. A company should periodically design its network (every few years) based on precise knowledge of what customer types need and which activities add value.

To maximize on the optimum profitability, businesses intending to compete must lean on a robust model that incorporates all relevant variables and constraints. Supply chains can typically reduce logistics costs by up to 7% while maintaining or even raising service levels with an in-house linear program model.

The pace at which supply chains have been incorporating new business models has greatly accelerated over the past 10 years as gains in technology have boomed. Now more than ever, supply chain management is evolving into a cross-functional activity. Teams will have to interact more closely with other functional areas to identify the factors that influence self-induced volatility, customer profitability and network hemorrhaging, and agree on actions to manage them better.

The answer in this era is not subscribing to complicated precepts but being able to translate information into action and using language that is easy to understand.